| > plenty of evidence … although not qualitative or obviously causal Those two things are the opposite of each other (evidence, but only anecdotally; you cant be both). Anyway. More tangible to your argument; what is your argument that this will be more effective than just prompt engineering? Ive long believed that prompt engineering is a losers game; if there is a trivial set of tricks that improve the output, they will simply be automatically applied. We see this playing out with the system prompts in coding agents and image gen. The value of learning “photo realistic studio lighting…” was non existent. The nano banana api is capable of taking a naive prompt and expanding it with these tricks. People who devoted themselves to learning these “magical incantations” wasted their time and effort; and it was obvious, from the beginning this would be true. Now. With managing agents; if a trivial set of management tricks can drastically improve the results, why are you better off learning them now, rather than waiting for them to be baked into cursor/codex/claude in easy mode? What makes you believe this is a valuable investment in time and effort? Even if we accept that right now assigning personas to agents and managing them as a manager yields good results, the horizon for change right now is so short, it seems extraordinary to suggest mass management and leadership training for engineers. We should just wait and see. All in investments like this would just be tokenmaxing in a funny hat. |